| Title: | Daily steps are a predictor of, but perhaps not a risk factor for Parkinson's disease: findings from the UK Biobank |
| Journal: | npj Parkinson's Disease |
| Published: | 24 Nov 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41285792/ |
| DOI: | https://doi.org/10.1038/s41531-025-01214-6 |
| URL: | https://www.nature.com/articles/s41531-025-01214-6_reference.pdf |
Publication 18794
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Abstract
Previous studies link lower physical activity with incident Parkinson's disease (PD) but rely on self-reported data and fail to address reverse causation. This study used accelerometer-derived daily step count, an objective measure of physical activity, to examine its association with incident PD in the UK Biobank, within successive periods of follow-up. PD cases were identified through hospital inpatient and death data, and associated with machine learning-derived step counts using Cox regression models, adjusted for age, sex, demographic and lifestyle factors. For 94,696 valid participants and a median follow-up of 7.9 years, 407 incident PD cases occurred. Every 1000 steps higher were associated with 8% lower risk of PD (hazard ratio 0.92, 95% confidence interval 0.89-0.94). However, this association was no longer statistically significant when excluding follow-up periods closer to the time of accelerometer wear, suggesting that low activity may be an early marker, but not a risk factor for PD.</p>
11 Authors
- Aidan Acquah
- Andrew Creagh
- Valentin Hamy
- Alaina Shreves
- Charilaos Zisou
- Charlie Harper
- Stefan van Duijvenboden
- Chrystalina Antoniades
- Derrick Bennett
- David Clifton
- Aiden Doherty
1 Application
| Application ID | Title |
|---|---|
| 59070 | Statistical machine learning of wearable sensor data to predict disease outcomes |
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